Targeting Intervention for Healthcare-Associated Infections in Tennessee: Methods for Identifying and Communicating Facility-Specific Impact on Statewide Standardized Infection Ratios

BACKGROUND:   In Tennessee, seven healthcare-associated infection (HAI) events are reportable to the state via the National Healthcare Safety Network (NHSN), and data are regularly provided to the HAI Multidisciplinary Advisory Group (MDAG) to guide prevention efforts. In response to MDAG concern regarding sustaining improvement in the state standardized infection ratio (SIR) for certain HAIs, our aim was to explore methods to identify facilities for targeted intervention based on their impact on the state SIR, and to communicate this information to infection control staff.

METHODS:   Each facility's relative impact (RI) on the state SIR was calculated by determining the percent change in the state SIR when the facility's numerator and denominator data were included in the state calculations (SIR_TN) versus when the facility's data were removed (SIR_NEW):

• RI= (SIR_TN-SIR_NEW / SIR_TN) * 100
• SIR_NEW=( Obs_TN-Obs_FACILITY)/(Exp_TN-Exp_FACILITY), where
• Obs= observed (actual) number of infections, and
• Exp= number of predicted infections based on risk adjustment performed by NHSN

Additionally, we calculated the number of infections a facility would have needed to prevent (NNTP) in the reporting period of interest in order to meet each HHS National 5-year Prevention Target:

• NNTP = Obs_FACILITY - (Exp_FACILITY*HHS Goal SIR)

Results of each method were presented to the MDAG for feedback before sharing with hospitals.

RESULTS:   Relative impact was displayed on a bubble plot, in which each facility was represented by a circle with size proportional to the facility’s relative impact on the state SIR, with number of procedures or device days on the x-axis and SIR on the y-axis. The MDAG used this information to target outlying facilities for intervention. Additionally, a tabular facility-specific Prevention Report Card, which displayed the NNTP and other impact metrics (including whether the facility had a top-5 NNTP) for each reportable HAI, was created and distributed to facilities quarterly. A web-based calculator was posted on the TDH website <http://health.state.tn.us/ceds/HAI/calculator.shtml>, allowing facilities to calculate their NNTP in real time.

CONCLUSIONS:   By assessing the impact of each facility’s data on the state SIR, we identified facilities for which targeted prevention efforts may have the greatest opportunity to improve statewide metrics.  Additionally, providing these metrics directly to infection control staff is an important tool for facilities to implement data-driven prevention efforts.